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FDS FDS/CADMY Colloquium

FDS/CADMY Colloquium: Michael I. Jordan (Berkeley)

Speaker: Michael I. Jordan (Berkeley)

Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics

University of California, Berkeley

Tuesday, April 22, 2025

11:30AM - 1:00PM

Lunch at 11:30am in 1307
Talk at 12:00pm in 1327

and via Webcast: https://yale.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=0656e87c-e9b7-4b34-886d-b23000fd4926

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Speaker bio: Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley.

He received his Master’s degree in Mathematics from Arizona State University and earned his Ph.D. in Cognitive Science in 1985 from the University of California, San Diego. From 1988 to 1998, he was a professor at MIT.

Prof. Jordan’s research interests bridge the computational, statistical, cognitive, biological, and social sciences. He is a member of the National Academy of Sciences, the National Academy of Engineering, the American Academy of Arts and Sciences, and a Foreign Member of the Royal Society. Additionally, he is a Fellow of the American Association for the Advancement of Science.

Prof. Jordan has received numerous accolades, including:

  • The inaugural World Laureates Association (WLA) Prize (2022)
  • The Ulf Grenander Prize from the American Mathematical Society (2021)
  • The IEEE John von Neumann Medal (2020)
  • The IJCAI Research Excellence Award (2016)
  • The David E. Rumelhart Prize (2015)
  • The ACM/AAAI Allen Newell Award (2009)

In 2016, Science recognized Prof. Jordan as the “most influential computer scientist” worldwide, based on rankings from the Semantic Scholar search engine.

About the series: FDS has partnered with Center for Algorithms, Data, and Market Design at Yale (CADMY) for a series of talks. CADMY is an innovative research center at the intersection of computer science, economics, and data science.

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